# optimizer
optimizer = dict(type='SGD', lr=0.01, momentum=0.9, weight_decay=0.0005)
optimizer_config = dict(grad_clip=dict(max_norm=35, norm_type=2))
# learning policy
lr_config = dict(policy='poly', power=0.9, min_lr=1e-4, by_epoch=False)
# runtime settings
total_epochs = 80
# evaluation = dict(interval=2, metric=['mIoU', 'mAP'], pre_eval=True)
# evaluation = None
# runner = dict(type='IterBasedRunner', max_iters=80000)
# checkpoint_config = dict(save_best=True)
